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The increased speed and accuracy in solving optimization problems of gas allocation in the gas lift process are of high importance. Solving gas allocation optimization problems generally involves two steps: (1) The gas lift performance curve (GLPC) fitting (gas lift modeling) and (2) optimizing the allocation of gas between wells. Therefore, in order to increase the speed and accuracy of solving gas allocation optimization problems, both steps need to be improved. In order to increase the accuracy of the first step, a new correlation was proposed in which, in addition to increasing the accuracy of fit, the optimization speed was improved by decreasing the number of constants used in the correlation. Besides, in order to improve the performance of the second step, water cycle optimization algorithm was used and the results obtained from this algorithm were compared with the results obtained from previous studies on teaching–learning-based optimization (TLBO) algorithm, continuous ant colony (CACO) algorithm, genetic algorithm (GA) and particle swarm optimization algorithm (PSO) for solving the five-well Nishikiori index problem. The results suggested that the water cycle optimization algorithm has a very good performance in terms of convergence rate, non-capture at local optimum points and repeatability. Finally, as a new problem, the gas allocation between the wells of one of the heavy oil fields in the southwest of Iran was optimized with predetermined oil production rates. The goal of optimization was to obtain the minimum amount of gas required to produce the predetermined oil rates using the water cycle optimization algorithm. The results showed that optimization is of higher importance in lower oil production targets, resulting in higher additional oil production.

One way to reduce the costs of investment in underground natural gas storage processes is to replace a portion of the base gas with a cheap gas. Optimizing the replacement amount of the base gas is one of the most attractive issues as mixing between the replaced base gas and the working gas and exceeding the injection pressure above the formation fracturing pressure are the two important phenomena that can occur and limit the amount of base gas replacement. In the present study, the concept of smart gas is applied to alleviate the encountered limitations during base gas replacement. Smart gas is referred to as the gas, the composition of which is adjusted so as to obtain the maximum amount of the base gas replacement. In the present work, dry air is used as the candidate gas to study the base gas replacement process in a depleted gas reservoir. Due to the fact that execution of a large-scale compositional reservoir simulator incorporated with an optimization algorithm is a time-consuming process, in order to calculate the optimum composition of the candidate gases, a proxy model is applied as a computationally inexpensive alternative to full numerical simulation. The results reveal that the composition of CO2in air is an important parameter in controlling mixing between the candidate base gas and the working gas, while maintaining the injection pressure below the fracturing pressure of the formation. In addition, when the CO2composition exceeds a specific value (40.95% in the modified air), the pressure that is required for gas production at a target rate cannot be supplied. The optimization of the CO2composition in the candidate gas employing the proxy model shows that it is possible to replace 28.4% of the base gas and reach an enhanced gas recovery of about 18.55% in the reservoir under study using the optimized CO2composition of 20.08% in the modified air as the replacing gas.

Due to the significance of gas storage in recent years, the importance of its most crucial operational and economic aspect, the cushion gas, has come under great scrutiny. The cushion gas is injected into the reservoir to raise the pressure to a specific range, ensuring optimum rate and sufficient deliverability during the production phase. 20 to 70 % of the total gas in an underground gas storage (UGS) operation can be comprised of cushion gas, and it is widely known that it's the most expensive part of the procedure. If the natural gas itself is used as the cushion gas, it cannot be produced, reducing the efficiency of resource delivery to the consumer market. Consequently, nitrogen and carbon dioxide have been considered to replace a portion of the cushion gas. Although this application can prove beneficial, there are still gray areas that have not been addressed conclusively. This paper aims to categorize the advantages and disadvantages of the application of nitrogen and carbon dioxide as cushion gas from previous studies for the first time and provide future researchers with challenges that are yet to be resolved. Initially, a brief history of prior operations and studies is given. Secondly, the properties of nitrogen and carbon dioxide and their potential effect on the operation and mixing between cushion gas and working gas are discussed. After that, the operational parameters affecting the mixing phenomenon concerning each gas are presented, and future challenges and opportunities regarding the utilization of nitrogen and carbon dioxide as the cushion gas are introduced. It was concluded that the abnormal changes in CO2's properties, specifically density, and viscosity, can heavily impact the cushion gas selection process. Furthermore, an increase in production and injection rates can increase the mixing percentage. Simultaneous injection of cushion gas and working gas can potentially limit the mixing phenomenon and decrease the duration of the UGS process before it is ready for the initial production phase.